IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v51y2021i6p450-462.html
   My bibliography  Save this article

Choice-Based Dynamic Pricing for Vacation Rentals

Author

Listed:
  • Yaping Wang

    (Verizon, New York, New York 10007)

  • Kelly McGuire

    (ZS Associates, Washington District of Columbia 20814)

  • Jeremy Terbush

    (Simon Property Group, Indianapolis, Indiana 46204)

  • Michael Towns

    (RCI/Wyndham Destinations, Tuxedo Park, New York 10987)

  • Chris K. Anderson

    (SC Johnson College of Business, School of Administration, Cornell University, Ithaca, New York 14853)

Abstract

In this paper, we propose a new dynamic pricing approach for the vacation rental revenue management problem. The proposed approach is based on a conditional logistic regression that predicts the purchasing probability for rental units as a function of various factors, such as lead time, availability, property features, and market selling prices. In order to estimate the price sensitivity throughout the booking horizon, a rolling window technique is provided to smooth the impact over time and build a consistent estimation. We apply a nonlinear optimization algorithm to determine optimal prices to maximize the revenue, considering current demand, availability from both the rental company and its competitors, and the price sensitivity of the rental guest. A booking curve heuristic is used to align the booking pace with business targets and feed the adjustments back into the optimization routine. We illustrate the proposed approach by successfully applying it to the revenue management problem of Wyndham Destinations vacation rentals. Model performance is evaluated by pricing two regions within the Wyndham network for part of the 2018 vacation season, indicating revenue per unit growth of 3.5% and 5.2% (for the two regions) through model use.

Suggested Citation

  • Yaping Wang & Kelly McGuire & Jeremy Terbush & Michael Towns & Chris K. Anderson, 2021. "Choice-Based Dynamic Pricing for Vacation Rentals," Interfaces, INFORMS, vol. 51(6), pages 450-462, November.
    • Handle: RePEc:inm:orinte:v:51:y:2021:i:6:p:450-462
    DOI: 10.1287/inte.2021.1075
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2021.1075
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2021.1075?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Marcel L. Corstjens & David A. Gautschi, 1983. "Formal Choice Models in Marketing," Marketing Science, INFORMS, vol. 2(1), pages 19-56.
    2. Chris K. Anderson & Xiaoqing (Kristine) Xie, 2016. "Dynamic pricing in hospitality: overview and opportunities," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 9(2/3), pages 165-174.
    3. Guillermo Gallego & Richard Ratliff & Sergey Shebalov, 2015. "A General Attraction Model and Sales-Based Linear Program for Network Revenue Management Under Customer Choice," Operations Research, INFORMS, vol. 63(1), pages 212-232, February.
    4. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jing-Sheng Song & Zhengliang Xue, 2021. "Demand Shaping Through Bundling and Product Configuration: A Dynamic Multiproduct Inventory-Pricing Model," Operations Research, INFORMS, vol. 69(2), pages 525-544, March.
    2. Aldric Vives & Marta Jacob & Marga Payeras, 2018. "Revenue management and price optimization techniques in the hotel sector," Tourism Economics, , vol. 24(6), pages 720-752, September.
    3. Martin Petricek & Stepan Chalupa & David Melas, 2021. "Model of Price Optimization as a Part of Hotel Revenue Management—Stochastic Approach," Mathematics, MDPI, vol. 9(13), pages 1-16, July.
    4. Ozgun Caliskan Demirag & Ozgul Baysar & Pinar Keskinocak & Julie L. Swann, 2010. "The effects of customer rebates and retailer incentives on a manufacturer's profits and sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(1), pages 88-108, February.
    5. González-Benito, Óscar & Santos-Requejo, Libia, 2002. "A comparison of approaches to exploit budget allocation data in cross-sectional maximum likelihood estimation of multi-attribute choice models," Omega, Elsevier, vol. 30(5), pages 315-324, October.
    6. Vincent Mak & Amnon Rapoport & Eyran J. Gisches & Jiaojie Han, 2014. "Purchasing Scarce Products Under Dynamic Pricing: An Experimental Investigation," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 425-438, July.
    7. Benny Mantin & Daniel Granot & Frieda Granot, 2011. "Dynamic pricing under first order Markovian competition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(6), pages 608-617, September.
    8. Zhao, Ju & Qiu, Ju & Zhou, Yong-Wu & Hu, Xiao-Jian & Yang, Ai-Feng, 2020. "Quality disclosure in the presence of strategic consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    9. Tien Mai & Arunesh Sinha, 2022. "Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach," Papers 2204.11451, arXiv.org.
    10. Régis Chenavaz & Corina Paraschiv & Gabriel Turinici, 2017. "Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach," Working Papers hal-01592958, HAL.
    11. Dasci, A. & Karakul, M., 2009. "Two-period dynamic versus fixed-ratio pricing in a capacity constrained duopoly," European Journal of Operational Research, Elsevier, vol. 197(3), pages 945-968, September.
    12. Grigoriev, A. & Hiller, B. & Marban, S. & Vredeveld, T. & van der Zwaan, G.R.J., 2010. "Dynamic pricing problems with elastic demand," Research Memorandum 053, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    13. Shivaram Subramanian & Hanif Sherali, 2010. "A fractional programming approach for retail category price optimization," Journal of Global Optimization, Springer, vol. 48(2), pages 263-277, October.
    14. Vincent Mak & Amnon Rapoport & Eyran J. Gisches, 2018. "Dynamic Pricing Decisions and Seller-Buyer Interactions under Capacity Constraints," Games, MDPI, vol. 9(1), pages 1-23, February.
    15. Ibrahim Mohammed & Basak Denizci Guillet & Rob Law & Wassiuw Abdul Rahaman, 2021. "Predicting the direction of dynamic price adjustment in the Hong Kong hotel industry," Tourism Economics, , vol. 27(2), pages 346-364, March.
    16. Dong Li & Xiaojun Wang, 2017. "Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5127-5141, September.
    17. Chenavaz, Régis & Paraschiv, Corina, 2018. "Dynamic pricing for inventories with reference price effects," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-16.
    18. Yuri Levin & Jeff McGill & Mikhail Nediak, 2008. "Risk in Revenue Management and Dynamic Pricing," Operations Research, INFORMS, vol. 56(2), pages 326-343, April.
    19. Adam J. Mersereau & Dan Zhang, 2012. "Markdown Pricing with Unknown Fraction of Strategic Customers," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 355-370, July.
    20. Fernando Bernstein & Yang Li & Kevin Shang, 2016. "A Simple Heuristic for Joint Inventory and Pricing Models with Lead Time and Backorders," Management Science, INFORMS, vol. 62(8), pages 2358-2373, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:51:y:2021:i:6:p:450-462. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.